AI Medical Compendium Journal:
Rheumatology (Oxford, England)

Showing 11 to 20 of 24 articles

Deep learning-based automatic scoring models for the disease activity of rheumatoid arthritis based on multimodal ultrasound images.

Rheumatology (Oxford, England)
OBJECTIVES: We aimed to investigate the value of deep learning (DL) models based on multimodal ultrasonographic (US) images to quantify RA activity.

Artificial intelligence in osteoarthritis: repair by knee joint distraction shows association of pain, radiographic and immunological outcomes.

Rheumatology (Oxford, England)
OBJECTIVES: Knee joint distraction (KJD) has been associated with clinical and structural improvement and SF marker changes. The current objective was to analyse radiographic changes after KJD using an automatic artificial intelligence-based measurem...

A deep learning system for quantitative assessment of microvascular abnormalities in nailfold capillary images.

Rheumatology (Oxford, England)
OBJECTIVES: Nailfold capillaroscopy is key to timely diagnosis of SSc, but is often not used in rheumatology clinics because the images are difficult to interpret. We aimed to develop and validate a fully automated image analysis system to fill this ...

Deep learning algorithms for magnetic resonance imaging of inflammatory sacroiliitis in axial spondyloarthritis.

Rheumatology (Oxford, England)
OBJECTIVE: The aim of this study was to develop a deep learning algorithm for detection of active inflammatory sacroiliitis in short tau inversion recovery (STIR) sequence MRI.

Harnessing of real-world data and real-world evidence using digital tools: utility and potential models in rheumatology practice.

Rheumatology (Oxford, England)
The diversity of diseases in rheumatology and variability in disease prevalence necessitates greater data parity in disease presentation, treatment responses including adverse events to drugs and various comorbidities. Randomized controlled trials ar...